| 摘要: |
| 目的：高原肺水肿(HAPE)是一种可能危及生命的病症,主要影响快速登上高海拔地区的个体。本文旨在开发并验证一个用于儿童游客HAPE预测的模型,以便于早期识别和管理。方法： 本研究纳入了133名儿童,其中65名被诊断为HAPE,68名未患HAPE。采用逻辑回归分析来识别HAPE的显著预测因子。通过受试者工作特征(ROC)曲线、校准图和决策曲线分析(DCA)来评估模型性能。基于所识别的预测因子,构建了一个用于预测HAPE风险的列线图。结果： HAPE的主要预测因子包括年龄、BMI、症状出现天数、SpO2、呼吸频率、白细胞计数(WBC)、性别和发热。ROC曲线显示了较好的区分能力,曲线下面积(AUC)为0.871。校准分析表明预测概率与观察到的概率之间有良好的一致性(Hosmer-Lemeshow检验P= 0.5144166)。决策曲线分析强调了模型的临床实用性,特别是在0到0.5的阈值概率范围内显示出显著的净收益。列线图集成了关键预测因子,为儿童HAPE风险提供了一个直观和定量的评估方法。结论：该预测模型具有较高的准确性和临床实用性,能够实现HAPE的早期识别和干预。列线图为临床医生提供了一个实用工具,有助于决策过程,并可能改善处于HAPE风险中的儿童的预后。 |
| 关键词: HAPE, 儿童, 预测模型, 逻辑回归, 列线图, ROC曲线, 校准曲线, 决策曲线分析。 |
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| 基金项目:浙江省医学会临床医学科研专项资金项目（2023ZYC-A183） |
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| Develop and Validate: A Risk Assessment Model for High-Altitude Pulmonary Edema in Pediatric Tourists |
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liu lingke1, guo shengchun2,3,4, cai yanping2,3,4, ou guangyuan2,3,4, BAO Deyangzi2,3,4, LI Shouyuan2,3,4, PAN Boting1
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1.The Affiliated Hospital of Shaoxing University;2.People'3.'4.s Hospital of Dachaidan Administrative Committee
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| Abstract: |
| Objective: High-altitude pulmonary edema (HAPE) is a potentially life-threatening condition that primarily affects individuals who rapidly ascend to high altitudes. This study aims to develop and validate a model for predicting HAPE in pediatric tourists, facilitating early identification and management. Methods: A total of 133 children were included in this study, with 65 diagnosed with HAPE and 68 without HAPE. Logistic regression analysis was used to identify significant predictors of HAPE. The model"s performance was evaluated using receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA). A nomogram was constructed based on the identified predictors to predict HAPE risk. Results: The major predictors of HAPE included age, BMI, days of symptom onset, SpO2, respiratory rate, white blood cell count (WBC), gender, and fever. The ROC curve demonstrated good discriminative ability with an area under the curve (AUC) of 0.871. Calibration analysis indicated good agreement between predicted and observed probabilities (Hosmer-Lemeshow test P= 0.5144166). Decision curve analysis highlighted the model"s clinical utility, showing significant net benefit, particularly within a threshold probability range of 0 to 0.5. The nomogram integrated key predictors, providing an intuitive and quantitative method for assessing the risk of HAPE in children. Conclusion: The predictive model exhibits high accuracy and clinical utility, enabling early identification and intervention for HAPE. The nomogram offers clinicians a practical tool to aid in decision-making and may improve outcomes for children at risk of HAPE. |
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